This disclosure relates generally to revenue assurance, and more particularly to analytical techniques for improved revenue assurance.
Revenue assurance is important to many service industries, by requiring reconciliation between records in multiple data feeds to identify discrepancies in records that would lead to revenue leakage or over-billing of a service. In the telecommunications industry, for example, billable telephony records can be reconciled with the base signaling records as the billable telephony records pass through an organization's data collection, guiding, rating, and billing stages before the call appears as a line item on the customer's bill. Common issues include dropped billing records, incorrect start and end times, incorrect rating of the event, or inability to guide the billable record to the appropriate billable account. It has been estimated that as much as seven to fifteen percent of a telecommunications company's service goes unbilled due to revenue assurance issues.
Another example is related to web content delivery (e.g., ringtones, wallpapers, video clips, etc.), where the content is owned by third parties. Mobile companies are billed for their end customer's downloads and must ensure appropriate billing of the end customers. In yet another example, in the utilities industry, upwards of five to ten percent of capacity goes unbilled due to line leakage, un-metered lines, faulty metering equipment, or fraud.
Detection of revenue assurance issues is paramount to an organization, and of importance for the profitability of the organization, yet also for compliance with numerous regulatory or governmental requirements, such as the Sarbanes-Oxley Act (SOX), among others. Unfortunately, current techniques for detecting and resolving revenue assurance issues are inefficient, costly, and of limited effectiveness.